
<h1><span class="yiyi-st" id="yiyi-12">numpy.random.RandomState</span></h1>
        <blockquote>
        <p>原文：<a href="https://docs.scipy.org/doc/numpy/reference/generated/numpy.random.RandomState.html">https://docs.scipy.org/doc/numpy/reference/generated/numpy.random.RandomState.html</a></p>
        <p>译者：<a href="https://github.com/wizardforcel">飞龙</a> <a href="http://usyiyi.cn/">UsyiyiCN</a></p>
        <p>校对：（虚位以待）</p>
        </blockquote>
    
<dl class="class">
<dt id="numpy.random.RandomState"><span class="yiyi-st" id="yiyi-13"> <em class="property">class </em><code class="descclassname">numpy.random.</code><code class="descname">RandomState</code></span></dt>
<dd><p><span class="yiyi-st" id="yiyi-14">Mersenne Twister伪随机数生成器的容器。</span></p>
<p><span class="yiyi-st" id="yiyi-15"><a class="reference internal" href="#numpy.random.RandomState" title="numpy.random.RandomState"><code class="xref py py-obj docutils literal"><span class="pre">RandomState</span></code></a>提供多种方法，用于生成从各种概率分布中抽取随机数。</span><span class="yiyi-st" id="yiyi-16">除了特定于分布的参数之外，每个方法都使用缺省为<code class="docutils literal"><span class="pre">None</span></code>的关键字参数<em class="xref py py-obj">size</em>。</span><span class="yiyi-st" id="yiyi-17">如果<em class="xref py py-obj">size</em>为<code class="docutils literal"><span class="pre">None</span></code>，则生成并返回单个值。</span><span class="yiyi-st" id="yiyi-18">如果<em class="xref py py-obj">size</em>是整数，则返回填充有生成值的1-D数组。</span><span class="yiyi-st" id="yiyi-19">如果<em class="xref py py-obj">size</em>是元组，则填充并返回具有该形状的数组。</span></p>
<p><span class="yiyi-st" id="yiyi-20"><em>兼容性保证</em> 固定种子并使用相同参数的“RandomState”方法的固定顺序调用将始终产生相同的结果，直到四舍五入错误，除非值不正确。</span><span class="yiyi-st" id="yiyi-21">不正确的值将被修复，NumPy版本将在相关的docstring中注明。</span><span class="yiyi-st" id="yiyi-22">只要以前的行为保持不变，就允许扩展现有参数范围和添加新参数。</span></p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name">
<col class="field-body">
<tbody valign="top">
<tr class="field-odd field"><th class="field-name"><span class="yiyi-st" id="yiyi-23">参数：</span></th><td class="field-body"><p class="first"><span class="yiyi-st" id="yiyi-24"><strong>seed</strong>：{None，int，array_like}，可选</span></p>
<blockquote class="last">
<div><p><span class="yiyi-st" id="yiyi-25">随机种子，初始化伪随机数生成器。</span><span class="yiyi-st" id="yiyi-26">可以是整数，任何长度的数组（或其他序列）的整数，或<code class="docutils literal"><span class="pre">None</span></code>（默认值）。</span><span class="yiyi-st" id="yiyi-27">当<a class="reference internal" href="numpy.random.seed.html#numpy.random.seed" title="numpy.random.seed"><code class="xref py py-obj docutils literal"><span class="pre">seed</span></code></a>为<code class="docutils literal"><span class="pre">None</span></code>时，如果<code class="docutils literal"><span class="pre">/dev/urandom</span></code>（在Windows上，则为类似的文件）可用，则<a class="reference internal" href="#numpy.random.RandomState" title="numpy.random.RandomState"><code class="xref py py-obj docutils literal"><span class="pre">RandomState</span></code></a>将尝试从它读取，否则从时钟设置种子。</span></p>
</div></blockquote>
</td>
</tr>
</tbody>
</table>
<p class="rubric"><span class="yiyi-st" id="yiyi-28">注</span></p>
<p><span class="yiyi-st" id="yiyi-29">Python stdlib模块“random”也包含Mersenne Twister伪随机数生成器，其中有许多方法与<a class="reference internal" href="#numpy.random.RandomState" title="numpy.random.RandomState"><code class="xref py py-obj docutils literal"><span class="pre">RandomState</span></code></a>中提供的方法类似。</span><span class="yiyi-st" id="yiyi-30"><a class="reference internal" href="#numpy.random.RandomState" title="numpy.random.RandomState"><code class="xref py py-obj docutils literal"><span class="pre">RandomState</span></code></a>除了具有NumPy感知之外，还具有一个优点是提供更多数量的概率分布以供选择。</span></p>
<p class="rubric"><span class="yiyi-st" id="yiyi-31">方法</span></p>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
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<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-32"><a class="reference internal" href="numpy.random.RandomState.beta.html#numpy.random.RandomState.beta" title="numpy.random.RandomState.beta"><code class="xref py py-obj docutils literal"><span class="pre">beta</span></code></a>(a, b[, size])</span></td>
<td><span class="yiyi-st" id="yiyi-33">从Beta分布抽取样本。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-34"><a class="reference internal" href="numpy.random.RandomState.binomial.html#numpy.random.RandomState.binomial" title="numpy.random.RandomState.binomial"><code class="xref py py-obj docutils literal"><span class="pre">binomial</span></code></a>(n, p[, size])</span></td>
<td><span class="yiyi-st" id="yiyi-35">从二项分布抽取样本。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-36"><a class="reference internal" href="numpy.random.RandomState.bytes.html#numpy.random.RandomState.bytes" title="numpy.random.RandomState.bytes"><code class="xref py py-obj docutils literal"><span class="pre">bytes</span></code></a>(length)</span></td>
<td><span class="yiyi-st" id="yiyi-37">返回随机字节。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-38"><a class="reference internal" href="numpy.random.RandomState.chisquare.html#numpy.random.RandomState.chisquare" title="numpy.random.RandomState.chisquare"><code class="xref py py-obj docutils literal"><span class="pre">chisquare</span></code></a>(df[, size])</span></td>
<td><span class="yiyi-st" id="yiyi-39">从卡方分布抽取样本。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-40"><a class="reference internal" href="numpy.random.RandomState.choice.html#numpy.random.RandomState.choice" title="numpy.random.RandomState.choice"><code class="xref py py-obj docutils literal"><span class="pre">choice</span></code></a>(a[, size, replace, p])</span></td>
<td><span class="yiyi-st" id="yiyi-41">从给定的1-D数组生成随机样本</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-42"><a class="reference internal" href="numpy.random.RandomState.dirichlet.html#numpy.random.RandomState.dirichlet" title="numpy.random.RandomState.dirichlet"><code class="xref py py-obj docutils literal"><span class="pre">dirichlet</span></code></a>（alpha [，size]）</span></td>
<td><span class="yiyi-st" id="yiyi-43">从Dirichlet分布绘制样本。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-44"><a class="reference internal" href="numpy.random.RandomState.exponential.html#numpy.random.RandomState.exponential" title="numpy.random.RandomState.exponential"><code class="xref py py-obj docutils literal"><span class="pre">exponential</span></code></a>（[scale，size]）</span></td>
<td><span class="yiyi-st" id="yiyi-45">从指数分布绘制样本。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-46"><a class="reference internal" href="numpy.random.RandomState.f.html#numpy.random.RandomState.f" title="numpy.random.RandomState.f"><code class="xref py py-obj docutils literal"><span class="pre">f</span></code></a>(dfnum, dfden[, size])</span></td>
<td><span class="yiyi-st" id="yiyi-47">从F分布绘制样本。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-48"><a class="reference internal" href="numpy.random.RandomState.gamma.html#numpy.random.RandomState.gamma" title="numpy.random.RandomState.gamma"><code class="xref py py-obj docutils literal"><span class="pre">gamma</span></code></a>(shape[, scale, size])</span></td>
<td><span class="yiyi-st" id="yiyi-49">从Gamma分布绘制样本。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-50"><a class="reference internal" href="numpy.random.RandomState.geometric.html#numpy.random.RandomState.geometric" title="numpy.random.RandomState.geometric"><code class="xref py py-obj docutils literal"><span class="pre">geometric</span></code></a>(p[, size])</span></td>
<td><span class="yiyi-st" id="yiyi-51">从几何分布绘制样本。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-52"><a class="reference internal" href="numpy.random.RandomState.get_state.html#numpy.random.RandomState.get_state" title="numpy.random.RandomState.get_state"><code class="xref py py-obj docutils literal"><span class="pre">get_state</span></code></a>()</span></td>
<td><span class="yiyi-st" id="yiyi-53">返回一个元组，表示生成器的内部状态。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-54"><a class="reference internal" href="numpy.random.RandomState.gumbel.html#numpy.random.RandomState.gumbel" title="numpy.random.RandomState.gumbel"><code class="xref py py-obj docutils literal"><span class="pre">gumbel</span></code></a>([loc, scale, size])</span></td>
<td><span class="yiyi-st" id="yiyi-55">从Gumbel分布绘制样本。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-56"><a class="reference internal" href="numpy.random.RandomState.hypergeometric.html#numpy.random.RandomState.hypergeometric" title="numpy.random.RandomState.hypergeometric"><code class="xref py py-obj docutils literal"><span class="pre">hypergeometric</span></code></a>(ngood, nbad, nsample[, size])</span></td>
<td><span class="yiyi-st" id="yiyi-57">从超几何分布绘制样本。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-58"><a class="reference internal" href="numpy.random.RandomState.laplace.html#numpy.random.RandomState.laplace" title="numpy.random.RandomState.laplace"><code class="xref py py-obj docutils literal"><span class="pre">laplace</span></code></a>([loc, scale, size])</span></td>
<td><span class="yiyi-st" id="yiyi-59">从拉普拉斯或指定位置（或平均值）和比例（衰减）的双指数分布绘制样本。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-60"><a class="reference internal" href="numpy.random.RandomState.logistic.html#numpy.random.RandomState.logistic" title="numpy.random.RandomState.logistic"><code class="xref py py-obj docutils literal"><span class="pre">logistic</span></code></a>([loc, scale, size])</span></td>
<td><span class="yiyi-st" id="yiyi-61">从逻辑分布绘制样本。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-62"><a class="reference internal" href="numpy.random.RandomState.lognormal.html#numpy.random.RandomState.lognormal" title="numpy.random.RandomState.lognormal"><code class="xref py py-obj docutils literal"><span class="pre">lognormal</span></code></a>([mean, sigma, size])</span></td>
<td><span class="yiyi-st" id="yiyi-63">从对数正态分布绘制样本。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-64"><a class="reference internal" href="numpy.random.RandomState.logseries.html#numpy.random.RandomState.logseries" title="numpy.random.RandomState.logseries"><code class="xref py py-obj docutils literal"><span class="pre">logseries</span></code></a>(p[, size])</span></td>
<td><span class="yiyi-st" id="yiyi-65">从对数系列分布绘制样本。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-66"><a class="reference internal" href="numpy.random.RandomState.multinomial.html#numpy.random.RandomState.multinomial" title="numpy.random.RandomState.multinomial"><code class="xref py py-obj docutils literal"><span class="pre">multinomial</span></code></a>(n, pvals[, size])</span></td>
<td><span class="yiyi-st" id="yiyi-67">从多项分布绘制样本。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-68"><a class="reference internal" href="numpy.random.RandomState.multivariate_normal.html#numpy.random.RandomState.multivariate_normal" title="numpy.random.RandomState.multivariate_normal"><code class="xref py py-obj docutils literal"><span class="pre">multivariate_normal</span></code></a>(mean, cov[, size])</span></td>
<td><span class="yiyi-st" id="yiyi-69">从多变量正态分布绘制随机样本。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-70"><a class="reference internal" href="numpy.random.RandomState.negative_binomial.html#numpy.random.RandomState.negative_binomial" title="numpy.random.RandomState.negative_binomial"><code class="xref py py-obj docutils literal"><span class="pre">negative_binomial</span></code></a>(n, p[, size])</span></td>
<td><span class="yiyi-st" id="yiyi-71">从负二项分布绘制样本。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-72"><a class="reference internal" href="numpy.random.RandomState.noncentral_chisquare.html#numpy.random.RandomState.noncentral_chisquare" title="numpy.random.RandomState.noncentral_chisquare"><code class="xref py py-obj docutils literal"><span class="pre">noncentral_chisquare</span></code></a>(df, nonc[, size])</span></td>
<td><span class="yiyi-st" id="yiyi-73">从非中心卡方分布绘制样本。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-74"><a class="reference internal" href="numpy.random.RandomState.noncentral_f.html#numpy.random.RandomState.noncentral_f" title="numpy.random.RandomState.noncentral_f"><code class="xref py py-obj docutils literal"><span class="pre">noncentral_f</span></code></a>(dfnum, dfden, nonc[, size])</span></td>
<td><span class="yiyi-st" id="yiyi-75">从非中心F分布中抽取样本。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-76"><a class="reference internal" href="numpy.random.RandomState.normal.html#numpy.random.RandomState.normal" title="numpy.random.RandomState.normal"><code class="xref py py-obj docutils literal"><span class="pre">normal</span></code></a>([loc, scale, size])</span></td>
<td><span class="yiyi-st" id="yiyi-77">从正态（高斯）分布绘制随机样本。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-78"><a class="reference internal" href="numpy.random.RandomState.pareto.html#numpy.random.RandomState.pareto" title="numpy.random.RandomState.pareto"><code class="xref py py-obj docutils literal"><span class="pre">pareto</span></code></a>(a[, size])</span></td>
<td><span class="yiyi-st" id="yiyi-79">从具有指定形状的Pareto II或Lomax分布绘制样品。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-80"><a class="reference internal" href="numpy.random.RandomState.permutation.html#numpy.random.RandomState.permutation" title="numpy.random.RandomState.permutation"><code class="xref py py-obj docutils literal"><span class="pre">permutation</span></code></a>(x)</span></td>
<td><span class="yiyi-st" id="yiyi-81">随机置换序列，或返回置换范围。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-82"><a class="reference internal" href="numpy.random.RandomState.poisson.html#numpy.random.RandomState.poisson" title="numpy.random.RandomState.poisson"><code class="xref py py-obj docutils literal"><span class="pre">poisson</span></code></a>([lam, size])</span></td>
<td><span class="yiyi-st" id="yiyi-83">从泊松分布绘制样本。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-84"><a class="reference internal" href="numpy.random.RandomState.power.html#numpy.random.RandomState.power" title="numpy.random.RandomState.power"><code class="xref py py-obj docutils literal"><span class="pre">power</span></code></a>(a[, size])</span></td>
<td><span class="yiyi-st" id="yiyi-85">从具有正指数a-1的功率分布中在[0，1]中绘制样本。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-86"><a class="reference internal" href="numpy.random.RandomState.rand.html#numpy.random.RandomState.rand" title="numpy.random.RandomState.rand"><code class="xref py py-obj docutils literal"><span class="pre">rand</span></code></a>(d0, d1, ..., dn)</span></td>
<td><span class="yiyi-st" id="yiyi-87">给定形状中的随机值。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-88"><a class="reference internal" href="numpy.random.RandomState.randint.html#numpy.random.RandomState.randint" title="numpy.random.RandomState.randint"><code class="xref py py-obj docutils literal"><span class="pre">randint</span></code></a>(low[, high, size, dtype])</span></td>
<td><span class="yiyi-st" id="yiyi-89">将随机整数从<em class="xref py py-obj">低</em>（包括）返回到<em class="xref py py-obj">高</em>（不包含）。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-90"><a class="reference internal" href="numpy.random.RandomState.randn.html#numpy.random.RandomState.randn" title="numpy.random.RandomState.randn"><code class="xref py py-obj docutils literal"><span class="pre">randn</span></code></a>(d0, d1, ..., dn)</span></td>
<td><span class="yiyi-st" id="yiyi-91">从“标准正态”分布返回样本（或样本）。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-92"><a class="reference internal" href="numpy.random.RandomState.random_integers.html#numpy.random.RandomState.random_integers" title="numpy.random.RandomState.random_integers"><code class="xref py py-obj docutils literal"><span class="pre">random_integers</span></code></a>(low[, high, size])</span></td>
<td><span class="yiyi-st" id="yiyi-93"><em class="xref py py-obj">低</em>和<em class="xref py py-obj">高</em>之间的np.int类型的随机整数（含）。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-94"><a class="reference internal" href="numpy.random.RandomState.random_sample.html#numpy.random.RandomState.random_sample" title="numpy.random.RandomState.random_sample"><code class="xref py py-obj docutils literal"><span class="pre">random_sample</span></code></a>([size])</span></td>
<td><span class="yiyi-st" id="yiyi-95">在半开间隔[0.0，1.0]中返回随机浮点数。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-96"><a class="reference internal" href="numpy.random.RandomState.rayleigh.html#numpy.random.RandomState.rayleigh" title="numpy.random.RandomState.rayleigh"><code class="xref py py-obj docutils literal"><span class="pre">rayleigh</span></code></a>([scale, size])</span></td>
<td><span class="yiyi-st" id="yiyi-97">从瑞利分布绘制样本。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-98"><a class="reference internal" href="numpy.random.RandomState.seed.html#numpy.random.RandomState.seed" title="numpy.random.RandomState.seed"><code class="xref py py-obj docutils literal"><span class="pre">seed</span></code></a>([seed])</span></td>
<td><span class="yiyi-st" id="yiyi-99">种子生成器。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-100"><a class="reference internal" href="numpy.random.RandomState.set_state.html#numpy.random.RandomState.set_state" title="numpy.random.RandomState.set_state"><code class="xref py py-obj docutils literal"><span class="pre">set_state</span></code></a>(state)</span></td>
<td><span class="yiyi-st" id="yiyi-101">从一个元组设置发生器的内部状态。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-102"><a class="reference internal" href="numpy.random.RandomState.shuffle.html#numpy.random.RandomState.shuffle" title="numpy.random.RandomState.shuffle"><code class="xref py py-obj docutils literal"><span class="pre">shuffle</span></code></a>(x)</span></td>
<td><span class="yiyi-st" id="yiyi-103">通过随机播放其内容来修改序列。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-104"><a class="reference internal" href="numpy.random.RandomState.standard_cauchy.html#numpy.random.RandomState.standard_cauchy" title="numpy.random.RandomState.standard_cauchy"><code class="xref py py-obj docutils literal"><span class="pre">standard_cauchy</span></code></a>([size])</span></td>
<td><span class="yiyi-st" id="yiyi-105">从模式= 0的标准Cauchy分布绘制样本。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-106"><a class="reference internal" href="numpy.random.RandomState.standard_exponential.html#numpy.random.RandomState.standard_exponential" title="numpy.random.RandomState.standard_exponential"><code class="xref py py-obj docutils literal"><span class="pre">standard_exponential</span></code></a>([size])</span></td>
<td><span class="yiyi-st" id="yiyi-107">从标准指数分布绘制样本。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-108"><a class="reference internal" href="numpy.random.RandomState.standard_gamma.html#numpy.random.RandomState.standard_gamma" title="numpy.random.RandomState.standard_gamma"><code class="xref py py-obj docutils literal"><span class="pre">standard_gamma</span></code></a>(shape[, size])</span></td>
<td><span class="yiyi-st" id="yiyi-109">从标准Gamma分布绘制样本。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-110"><a class="reference internal" href="numpy.random.RandomState.standard_normal.html#numpy.random.RandomState.standard_normal" title="numpy.random.RandomState.standard_normal"><code class="xref py py-obj docutils literal"><span class="pre">standard_normal</span></code></a>（[size]）</span></td>
<td><span class="yiyi-st" id="yiyi-111">从标准正态分布绘制样品（平均值= 0，stdev = 1）。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-112"><a class="reference internal" href="numpy.random.RandomState.standard_t.html#numpy.random.RandomState.standard_t" title="numpy.random.RandomState.standard_t"><code class="xref py py-obj docutils literal"><span class="pre">standard_t</span></code></a>(df[, size])</span></td>
<td><span class="yiyi-st" id="yiyi-113">从具有<em class="xref py py-obj">df</em>自由度的标准学生t分布绘制样本。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-114"><a class="reference internal" href="numpy.random.RandomState.tomaxint.html#numpy.random.RandomState.tomaxint" title="numpy.random.RandomState.tomaxint"><code class="xref py py-obj docutils literal"><span class="pre">tomaxint</span></code></a>([size])</span></td>
<td><span class="yiyi-st" id="yiyi-115">0和<code class="docutils literal"><span class="pre">sys.maxint</span></code>之间的随机整数，包括0和。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-116"><a class="reference internal" href="numpy.random.RandomState.triangular.html#numpy.random.RandomState.triangular" title="numpy.random.RandomState.triangular"><code class="xref py py-obj docutils literal"><span class="pre">triangular</span></code></a>(left, mode, right[, size])</span></td>
<td><span class="yiyi-st" id="yiyi-117">从三角分布绘制样本。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-118"><a class="reference internal" href="numpy.random.RandomState.uniform.html#numpy.random.RandomState.uniform" title="numpy.random.RandomState.uniform"><code class="xref py py-obj docutils literal"><span class="pre">uniform</span></code></a>([low, high, size])</span></td>
<td><span class="yiyi-st" id="yiyi-119">从均匀分布绘制样本。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-120"><a class="reference internal" href="numpy.random.RandomState.vonmises.html#numpy.random.RandomState.vonmises" title="numpy.random.RandomState.vonmises"><code class="xref py py-obj docutils literal"><span class="pre">vonmises</span></code></a>(mu, kappa[, size])</span></td>
<td><span class="yiyi-st" id="yiyi-121">从von Mises分布绘制样本。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-122"><a class="reference internal" href="numpy.random.RandomState.wald.html#numpy.random.RandomState.wald" title="numpy.random.RandomState.wald"><code class="xref py py-obj docutils literal"><span class="pre">wald</span></code></a>(mean, scale[, size])</span></td>
<td><span class="yiyi-st" id="yiyi-123">从Wald或反高斯分布绘制样本。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-124"><a class="reference internal" href="numpy.random.RandomState.weibull.html#numpy.random.RandomState.weibull" title="numpy.random.RandomState.weibull"><code class="xref py py-obj docutils literal"><span class="pre">weibull</span></code></a>(a[, size])</span></td>
<td><span class="yiyi-st" id="yiyi-125">从威布尔分布绘制样本。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-126"><a class="reference internal" href="numpy.random.RandomState.zipf.html#numpy.random.RandomState.zipf" title="numpy.random.RandomState.zipf"><code class="xref py py-obj docutils literal"><span class="pre">zipf</span></code></a>(a[, size])</span></td>
<td><span class="yiyi-st" id="yiyi-127">从Zipf分布绘制样本。</span></td>
</tr>
</tbody>
</table>
</dd></dl>
